Merchant Center & Feed Rebuild
Disapprovals cleared at source, GTIN, MPN and attribute gaps closed, and titles rewritten to lead with searched terms. Custom labels for margin, stock cover and seasonality.
Demand capture for London brands, starting in Merchant Center rather than the campaign builder.
Delivered remotely for brands across London and United Kingdom.
Google is where a decision that has already been made gets executed. Somebody in the UK types the product, or something close to it, and the only open question is which shop gets the order. That makes this a distribution problem, and for a Shopify store the distribution runs through Merchant Center — which is why the first weeks of a London account are spent in a feed rather than in a bidding strategy.
For a UK feed that means specifics. Prices must match the site including VAT, or you collect price mismatch disapprovals that quietly starve your best products. Shipping and returns policy configured in Merchant Center rather than left to Google's guess. GTIN and MPN gaps closed, which on a jewellery or specialist food catalogue is genuine work. Titles rewritten to lead with the words British buyers type, in British terms, because a feed that says sneakers does not appear for trainers. Then custom labels for margin, stock cover and season so the structure can act on commercial reality.
Structure comes next. Brand isolated into its own campaign and budget, because in a London market where a founder-led brand may have real search volume of its own, blended ROAS will otherwise flatter an account that is buying customers it already had. Shopping and PMax carry the catalogue with asset groups split by margin band. Search covers the queries a feed cannot reach. Bidding to contribution margin comes at the very end, and every target change carries a written reason.
The London-specific work is running Google across markets without letting one feed break another. A UK feed needs VAT-inclusive prices and UK shipping policy. A euro feed for EU targeting needs its own pricing, its own delivery times and — critically — a landed cost story that matches what the checkout will charge, or you buy clicks that abandon at the shipping step. We build feeds per market from Shopify Markets pricing rather than from currency conversion, keep the negative library shared so query waste is only solved once, and separate reporting so a strong UK account does not hide an EU one that is losing money. The calendar matters too: UK auction pressure builds from mid-November through Black Friday and again into the Boxing Day and January sale period, so budgets and tROAS targets are planned against that curve rather than adjusted after the fact from Albuquerque the following morning.
The same standard of work we run for every client — applied to a London brand’s realities.
Full service detailDisapprovals cleared at source, GTIN, MPN and attribute gaps closed, and titles rewritten to lead with searched terms. Custom labels for margin, stock cover and seasonality.
Branded demand isolated into its own campaign, budget and target so non-brand performance becomes visible. Competitor conquesting runs as a separate line, judged separately.
Asset groups split by margin band and product type instead of one catch-all, with listing-group bids, product exclusions and brand-term controls applied wherever PMax still allows them.
A weekly pass over search terms and PMax category reports, with a maintained shared negative library so budget stops leaking into research, DIY and job-seeker queries.
Merchant promotions, sale price annotations, shipping and returns policy setup, product ratings, and local inventory ads where you have stores worth feeding.
Targets set from margin per product group rather than a platform default, moved in controlled increments, with a written reason attached to every bid and budget change.
We do not work off a rate card. Every London engagement starts with a fixed statement of work — named deliverables, named dates, one number — written after we have looked at your store, not before. If a smaller first step would serve you better, we will say so.
Get this scopedMerchant Center diagnostics, attribute coverage, campaign overlap and wasted spend scored against ninety days of search terms. You get the findings whether you hire us or not.
Titles, attributes, product types and custom labels rebuilt before any campaign work. A perfectly structured account on a bad feed still shows the wrong products to the wrong queries.
Brand, non-brand, Shopping, PMax and Search rebuilt with hard budget boundaries and a shared negative library, so each line answers a different commercial question.
tROAS targets derived from contribution margin by product group and applied gradually, so the account keeps its learning instead of resetting it every Monday.
Weekly query mining, monthly feed reviews, then expansion into the categories the search data says you can profitably win. Nothing scales before the query set is clean.
Anonymised under NDA. Figures pulled from the client’s own analytics.
~$6M/yr DTC, 900+ SKUs across size and colour variants, US · Shopify Plus
Returns ran at 31% and refund cost consumed the entire paid media margin. One size chart image served 40 different fits, and 62% of add-to-carts started on a collection page that never showed variant availability. The named constraint: no new product photography budget, so every fix had to come out of the existing asset library and the review corpus.
~$9M/yr, 210 SKUs, US + AU · Shopify Plus (migrated from BigCommerce)
Meta ROAS had slid from 3.6x to 1.9x in a year and the team had spent twelve months buying new creative to fix it. The real cause was measurement: the BigCommerce checkout dropped 22% of purchase events and the Conversions API had never been installed, so both ad platforms were optimising on incomplete data. The named constraint: peak season was 14 weeks out, and the replatform had to be live and stable well before Black Friday traffic arrived.
“Six thousand products and a Shopping feed nobody had touched since it was first generated — a third of it was disapproved and we had no idea. They rebuilt the feed off our real product data, fixed the GTIN and size attributes, and split brand off from non-brand so I could finally see what we were actually paying to acquire. They also cut the broad 'baby clothes' terms that were eating a quarter of the budget on people who were nowhere near buying. Spend is roughly flat and non-brand search revenue has close to doubled.”
Thirty minutes with the strategist who would actually run your account. We screen-share your store, read your data live, and tell you the three highest-value things we can see from the outside.
Prefer to write it out? [email protected] gets a real reply the same business day, Mon-Fri, 9am-6pm MT.